Method and system to compensate for lamp intensity differences in a photolithographic inspection tool

ABSTRACT

An after develop inspection tool considers tool-to-tool variability when determining confidence score for wafers under inspection. A golden wafer is used to calculate a RGB signature as well as the slope of the individual RGB curves for different lamp intensities. These slopes are normalized in order to generate a compensation factor for red values and blue values within a signature. When a wafer is subsequently inspected at an ADI station using a different lamp, the test wafer RGB signature is likely captured at a different lamp intensity. Consequently, when comparing the signatures, the golden wafer RGB signature is adjusted by the compensation factors, based on the different lamp&#39;s intensity setting, and this adjusted RGB signature is then used to determine whether a defect exists on the test wafer.

FIELD OF INVENTION

The following invention relates to inspection equipment inphotolithographic environments and, more particularly, to automatedcontrol of such equipment.

BACKGROUND

The lithography process for fabricating semiconductor devices can bebroken down into three general steps: coating; align/expose, develop.After the develop step is completed, the wafer is inspected for defectswhich may have occurred in any of the three lithography process areas.Typical defects include problems with photo resist or ARC/BARC coating,edge bead processing, exposure, alignment, development, as well asdefects caused by contamination or handling, such as particles orscratches.

Although the chance of misprocessing at any single lithography step issmall, a typical wafer goes through 20 to 25 lithography steps.Excursions due to process equipment problems, mishandling, andcontamination can occur at each of these steps, so the cumulativeprobability of a wafer experiencing a yield-limiting defect becomessignificant. While most defects impact only a small area of the waferand do not require rework, some defects impact 30% or more of the wafer.These are defined as global defects. After develop inspection (ADI)procedures detect, classify, and disposition wafers with globallithography defects for rework. Each recovered wafer can result insavings of thousands, or even tens of thousands of dollars, in revenue.

The vast majority of economically re-workable defects are macro-scale,as they are very large relative to the transistors and interconnectstructures in the device. Because of their large size, trained operatorsat microscope stations have traditionally detected macro defectsvisually. Since manual inspection is a relatively slow process comparedto track and stepper throughput, visual inspection has typically beenperformed on a limited lot-to-lot or within-lot sampling basis.Automating the ADI process for improved throughput has been achallenging problem, as macro defects vary widely in size, type, andappearance, requiring sensitive detection and sophisticated automaticdefect classification systems.

In typical systems, after various coating, align/expose, and developsteps, the wafers are delivered to an inspection station that captures aseries of whole wafer images using simultaneous dark and bright fieldillumination. A full-color image of 100% of the wafer is captured and isknown as a RGB signature. Such a signature has three elements: a redvalue, a green value, and a blue value that vary within a predeterminedrange such as 0-255. The resulting image or signature is compared tothat of a “golden” wafer with no defects and a confidence score isassigned indicating how similar the signatures are. When a significantdifference is detected, further analysis is performed to classify thedefect so that appropriate remedial action can be performed.

One shortcoming of the prior art ADI systems is that they do not accountfor the tool-to-tool variability in lamp output, or intensity, among thedifferent inspection tools. This variability affects the resulting RGBsignature and its values. Thus, a wafer can have a signature thatdiffers from the golden wafer image even if no misprocessing hasoccurred. This difference between a test wafer's image and the goldenwafer image may mistakenly be attributed to a defect even when there isno defect actually present.

Another shortcoming is that when a new ADI tool arrives at a facilityits factory settings may vary from the other tools already on theproduction line and this variance may be significant enough to causeerrors when inspecting wafers. Such as, for example, determining that awafer has a defect when one actually is not present on the wafer.

SUMMARY OF THE INVENTION

Accordingly, embodiments of the present invention relate to an ADI tooland method for its use that considers tool-to-tool lamp variability whenevaluating test wafers for defects. The image of a golden wafer is usedto calculate a RGB signature at a predetermined lamp intensity as wellas the respective slopes of the individual RGB curves for different lampintensities. These slopes are normalized in order to generate acompensation factor for red values and blue values to apply to a RGBsignature. When a wafer is subsequently inspected at an ADI stationusing a different lamp, the test wafer RGB signature is likely capturedat a different lamp intensity. Consequently, when comparing thesignatures, the golden wafer RGB signature is adjusted by thecompensation factors, based on the different lamp's intensity setting,and this adjusted RGB signature is then used to determine whether adefect exists on the test wafer.

One aspect of the present invention relates to an after developinspection (ADI) system that includes a first memory and an ADI tool.The first memory stores a first image signature of a golden waferacquired with a first lamp at a first intensity, and the ADI tool iscontrollable to capture a second image signature of a test wafer at asecond intensity using a second lamp. This system also includes an imagesignature adjuster, in communication with the first memory, configuredto generate an adjusted golden wafer signature by adjusting the firstimage signature based on a difference between the first intensity andthe second intensity. Additionally, a defect analyzer is provided thatis in communication with the after develop inspection tool and the imagesignature adjuster, and is configured to compare the second imagesignature with the adjusted golden wafer signature.

Another aspect of the present invention relates to a method forinspecting a photolithographically processed wafer. In accordance withthis aspect, a first image signature is determined for a golden waferusing a first lamp at a first intensity, and a second image signature isdetermined for the processed wafer using a second lamp at a secondintensity. The first image signature is then adjusted based on adifference between the first intensity and the second intensity togenerate an adjusted golden wafer signature. When generating a defectconfidence value, the second image signature is compared with theadjusted golden wafer signature instead of the first image signature.

Other embodiments and aspects relate to using similar RGB signatureanalysis to adjust and calibrate an ADI tool to more closely match otherADI tools on the same production line. Based on golden wafer signaturecomparisons, the gain levels of a new tool's detectors are adjusteduntil its RGB signature of the golden wafer matches a known signature.Additional advantages of the present invention will become readilyapparent to those skilled in this art from the following detaileddescription, wherein only the preferred embodiment of the invention isshown and described, simply by way of illustration of the best modecontemplated of carrying out the invention. As will be realized, theinvention is capable of other and different embodiments, and its severaldetails are capable of modifications in various obvious respects, allwithout departing from the invention. Accordingly, the drawings anddescription are to be regarded as illustrative in nature, and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a photolithographic fabricationenvironment in which embodiments of the present invention haveapplicability.

FIGS. 2A-2D are a graphical representation illustrating the effectvarying lamp intensity has on the values on a RGB signature for fourdifferent tools.

FIG. 3 depicts a flowchart of an exemplary algorithm to account fortool-to-tool lamp variability in an after develop inspection toolaccording to embodiments of the present invention.

FIG. 4 is a schematic illustration of an after develop inspection tool.

FIG. 5 depicts a flowchart of an exemplary algorithm to account andcompensate for tool-tool variability when matching a tool to anothertool.

FIG. 6 illustrates an exemplary computer architecture on whichembodiments of the present invention may be stored or executed.

DETAILED DESCRIPTION

During the photo lithography process, a wafer can undergo a variety ofcoating, exposing and developing steps. Also, throughout the process, anumber of different inspection tools can be used at various stages offabrication to perform ADI or other types of inspection.

FIG. 1 depicts a schematic view of an automated photo lithographysystem. In this system, a central control system 102 coordinates theoperation of the different processing stations 106, 110 and inspectiontools 108, 112. Furthermore, the central control system 102 likelycontrols the automated transport of wafers between the differentstations 106, 108, 110, 112, although such a mechanism is not explicitlydepicted in FIG. 1.

The control system 102 can be a programmable computer, or otherdedicated microcontroller in communication with each of the processstations 106, 110 and tools 108, 112. When fabricating a wafer, it willrun a process recipe and an inspection recipe, each of which specifiesthe steps and their order necessary to complete the fabrication of thewafer. These recipes can be stored at a central storage 104 of thecentral control system 102 and can either be executed by the centralcontrol system 102 to control a station 106, 110 or tool 108, 112, orcan be transmitted to the tool 106, 110 or station 108, 112 for remoteexecution. Furthermore, the recipes can be distributed to storage 120a-120 d locally connected to one of the stations 106, 110 or tools 108,112.

Each inspection tool 108, 112 has a distinct lamp that illuminates awafer being inspected. Each lamp has a number of settings that controlthe apparent brightness, or intensity, produced by the lamp. One way tomeasure the intensity of a lamp is through the use of a calibrationwafer. According to this technique, an image of the calibration wafer iscaptured at each of the lamp settings. As understood by one of ordinaryskill in this field, each such image can be characterized by a RGBsignature that varies based on the lamp setting. In particular, the G(green) signature component of each image is used to characterize thelamp intensity at each setting.

Table 1, below, shows a portion of the tabulation of output levels ofdifferent tool lamps. This partial table includes, by way of example, Gsignature values for lamp settings between 34-40. In addition, to thesespecific intensity values, the tabulation is performed for all thepossible settings of each lamp so as to characterize the lamp over itsentire range of settings. Such range of useable settings for ADI-relatedtools typically varies from about 10 through about 60.

TABLE 1 Tool #1 Lamp Tool #2 Lamp Lamp Setting Output Output 34 116 11435 119 117 36 121 120 37 123 122 38 128 127 39 131 131 40 133 135

This table correlating lamp intensity with a lamp setting can be storedat the storage 104 of the central control system 102, at each individualinspection tool, or both. Furthermore, there can be an individual tablefor each inspection tool, or a consolidated table for a plurality ofinspection tools 108, 112 with which the control system 102communicates.

As mentioned earlier, during device fabrication, a control system 102automates the process of inspection using what are known as “inspectionrecipes”. These recipes identify, at each inspection tool 108, 112, theproper lamp setting to create a signature to compare with the goldenwafer signature. Thus, the proper lamp setting during inspection isbased on the intensity at which the golden wafer image was captured.More particularly, an inspection recipe specifies the desired lampoutput level, such as the G signature value just described, and thecontrol system 102 automatically controls the inspection tool 108, 112lamp to select the appropriate lamp setting corresponding to therecipe's specified intensity.

For example, using the above table, a recipe requiring an output valueof 125 results in setting 37 on Tool #1 being chosen, resulting in alamp output of 123. However, if Tool #2 were being used, then setting 38would be chosen resulting in a lamp output of 127.

Because each lamp's actual output differs from the precise intensityused when capturing the golden wafer image, it induces differenttool-to-tool RGB color signatures for the test wafer even if the testwafer is substantially identical to the golden wafer. Thus, a defect maybe “found” even if none is present.

Experiments were performed that calculated the red, green and blueoutput data versus lamp intensity for each setting for a number oflamps. Thus, as shown in FIG. 2A for the particular lamp of Tool #1, RGBvalues are plotted over the various lamp settings (ranging fromapproximately 20-50). Using standard data-fitting techniques, thesevalues can be fitted to a line from which a slope is calculated. Ingeneral, as a lamp's intensity setting increases, the values for red,green and blue in the signature increase as well. Because of thevariation between the lamps, the resulting plot (see FIGS. 2A-2D) foreach tool will be different. For example, as the table above shows, theG output value for setting 37 varies between the two lamps (i.e., 123vs. 127); similar variance exists over all the lamp setting values asshown by the different plots.

However, by comparing the different plots for a variety of lamps, theexperiments showed that certain relationships between the slopes of theindividual red, green, blue curves remained substantially similar amongthe various lamps.

Using for example, the curves of FIG. 2D, the red curve 202D exhibits aslope of approximately 2.7; the green curve 204D exhibits a slope ofapproximately 3.2; and the blue curve 206D exhibits a slope ofapproximately 4.9. When these slopes are normalized with respect to thegreen value, the slopes become 0.8, 1.0 and 1.5, respectively. In otherwords, these ratios represent the change in one value that accompanies aunit change in the green value, the intensity of the lamp. FIGS. 2A-2Cdepict blue curves 202A-C, green curves 204A-C, and red curves 206A-Cfor three different lamps. Across these different lamps, the specificoutput values changed and even the slopes changed (as expected);however, the ratios between the RGB slopes remained consistently atapproximately 0.8, 1.0 and 1.5.

The table below shows exemplary results of tests involving the lamps offour different ADI tools.

TABLE 2 Raw Slope Normalized Slope Tool Red Green Blue Red Green Blue #12.8 3.5 5.6 0.8 1.0 1.6 #2 2.5 3 4.6 0.8 1.0 1.5 #3 2.5 2.9 4.4 0.9 1.01.5 #4 2.7 3.2 4.9 0.8 1.0 1.5These trends held true for a number of different calibration wafers aswell.

This consistent relationship between the individual RGB curves ofdifferent lamps can be utilized to compensate for tool-to-toolvariability when applying an inspection recipe at one or more ADI tools.Specifically, the flow chart in FIG. 3 depicts an exemplary algorithmthat ADI software on the central control system 102, or distributedamong the inspection tools 108, 112, can utilize to compensate fortool-to-fool variability.

In step 302, the software calculates the normalized RGB slopes for thegolden wafer. Alternatively, the normalized slopes could be calculatedusing a calibration wafer instead of the golden wafer. As explainedearlier, this would be accomplished by measuring the image signaturevalues, at the golden wafer station, for a number of lamp settings forthe individual red, green and blue values, fitting them to a respectiveline using conventional techniques, and then calculating the slopes andtheir normalized ratios. From these curves, a normalized slope for thered and blue components can be calculated; thereby indicating how thesecomponents of the RGB signature vary according to lamp intensity, or thegreen value for this lamp. The control system 102 would then store thesenormalized ratios to be used in later inspection steps.

In step 304, the RGB signature of the golden wafer is captured accordingto a specific lamp intensity specified in an inspection recipe. Ofcourse, in performing step 302, if the golden wafer is used, the RGBsignature of the golden wafer at the recipe's intensity is capturedanyway and, therefore, can be utilized without requiring step 304 to beexplicitly performed. This RGB signature of the golden wafer is storedby the control system 102 to be used in later inspection steps.

Next, in step 306, the ADI tool 108, 112 is used to test a wafer underproduction according to the inspection recipe. During this testing, theADI software selects the closest lamp setting, based on the recipe, andthen captures an image of the test wafer at this closest lamp intensity.The RGB signature of the test wafer is then calculated according toconventional methods.

Because the differences in lamp intensity can have an effect on theresulting RGB signature of the test wafer, a compensation step isperformed. In particular, in step 308, the ADI software adjusts the RGBsignature of the golden wafer according to the normalized ratioscalculated in step 302. This adjusting step can be performed by the ADIsoftware by retrieving from storage the normalized slope values and thegolden wafer signature. Also, the recipe lamp intensity value and theintensity actually used at the inspection tool would have to beretrieved and compared to calculate a difference. With this differencecalculated, the ADI software can easily adjust the RGB signature of thegolden wafer accordingly. For each unit of difference in the intensitybetween the recipe value and the actual inspection value, the red, greenand blue values of the golden wafer's RGB signature are adjustedaccording to the normalized ratios. As just described, the ADI softwaremay implement the image signature adjuster that generates the adjustedgolden wafer signature. However, such an adjuster may be implemented asa combination of software and hardware components as well.

It is this adjusted RGB signature that is compared to that of the testwafer, in step 310, when deciding whether a defect exists on the testwafer. Such a defect analyzer of the present invention contemplatesutilizing conventional comparison and confidence-scoring techniques toidentify the presence of defects as would be known to a skilled artisan.Typically, the respected values of the test wafer are compared todetermine if all three are within ±2 of their respective components ofthe golden wafer signature. Other threshold values can be used as well.

By way of example, assume that the normalized ratios calculated in step302 are 0.8, 1.0, and 1.5 as shown in Table 2. Furthermore, assume thatthe inspection recipe specifies that the golden wafer's image signatureis R:120, G:125, and B:160. Thus, the recipe specifies that the lampintensity of the inspection tool should be 125 when inspecting thewafer.

Assuming that the ADI Tool #1 is used (from Table 1), then setting 37 isselected for its lamp setting. At this setting, however, the actual lampintensity of the ADI tool is 123, not 125. The ADI tool then captures aRGB signature at this intensity setting. However, instead of comparingthe test wafer's RGB signature to R:120, G:125, and B:160, the goldenwafer signature is adjusted by the ADI software to compensate fortool-to-tool variability.

Specifically, the difference between 125 and 123 is −2. Thus, using thenormalized slope ratios, the red value is adjusted by (−2×0.8=−1.6) andthe blue value is adjusted by (−2×1.5=−3.0). Also, the green value isadjusted by the difference of −2. Therefore, the RGB signature of theinspected wafer is not compared to the original golden wafer signature;but, instead, is compared to R:118.4, G:123, B:157. From thiscomparison, the ADI tool generates a confidence score related to whetheror not a defect exists on the test wafer.

By comparing the inspected wafer signature and the adjusted golden wafersignature, the ADI software ignores changes in the inspected wafer's RGBsignature that are due to differences between the lamps of the ADItools. Thus, only changes in RGB signatures due to wafer processingdifferences are considered when determining whether a defect exists on awafer under inspection.

The previous description focused on compensating for lamp intensity anddetector variances within the environment of inspecting processedwafers. However, in addition to such uses, the same principles can bebeneficially used to perform tool-to-tool matching for an ADI toolbefore it is used to inspect processed wafers.

FIG. 4 depicts an exemplary ADI tool 400. Within a protective chamber414, a wafer 402 is supported on a platform 404 that is oftenrobotically controlled. As explained earlier, the tool 400 is anautomated apparatus having a controller 412 that may be a conventionalcomputer or other more-specialized hardware platform.

The controller 412 operates a lamp 406 and a detector 408. Inparticular, the controller 412 instructs the lamp 406 when to flash andat what intensity. The detector 408, which may be a CCD camera or othersimilar device, captures an image of the wafer 402 and transmits thisimage to the controller 412 for further processing.

As is well known to a skilled artisan, the detector 408 includes anadjustable gain level that affects the sensitivity of the detector 408.In a CCD for example, the gain level is used to adjust the count, orunits, that is output upon the reception of a certain number ofelectrons at a pixel. The adjustable gain control 410 is frequentlyimplemented as external knobs or other similar mechanisms 409 accessiblefrom the exterior of the detector 408. More automated detectors orcameras, however, may provide a system interface that can be accessedvia a display screen or interface port in order to adjust the gain levelvia software control. By adjusting the detector gain level, the red,green and blue values generated by the detector for a certain image areadjusted up or down. The detector gain control 410 is advantageouslyadjustable for each of the red, green, and blue values of the detector408. Typically, though, the green gain is not adjusted; instead the redand blue detector gain levels are adjusted as needed.

When a new ADI tool is introduced to a production line, matching the ADItool with other tools already in use may reduce the errors detected bythe new tool. FIG. 5 depicts an exemplary algorithm for performingtool-to-tool matching that relies on setting the red and blue detectorgain levels to appropriate values.

Using a golden wafer, one tool is used as a reference, in step 502, togenerate a RGB signature of the golden wafer. Such as, for example:R=120, G=125, B=160. Frequently, this golden wafer signature haspreviously been acquired and can be retrieved from an appropriatestorage location.

In step 504, the same golden wafer is used at the new tool to capture aRGB signature. Similar to before, the lamp of the new tool isadvantageously set to an intensity that is closest to that used for theearlier RGB signature of step 502. The new RGB signature of the goldenwafer will likely be different than the earlier one and, for example,may be: R=117, G=123, B=159.

The difference in the two golden wafer signatures are due, in part, todifferences in each tool's lamp and detector gain settings. Using thepreviously discussed methods, a series of images can be generated atdifferent lamp intensity settings in order to calculate, in step 506,the normalized RGB slopes for the lamp of the first, reference ADI tool.If this information has previously been calculated and stored, then itdoes not need to be re-created but can be retrieved from an appropriatestorage location.

In step 508, the normalized slopes are used by an image signatureadjuster to adjust the first golden wafer image based on the greenintensity of the second, or new, tool. For example, assuming the samenormalized ratios as before (i.e., R=0.8, G=1.0, B=1.5), the adjustedfirst golden wafer signature is calculated to be R=118.4, G=123, B=157.As before, the difference in the two green values is used in conjunctionwith the normalized slopes to calculate a respective factor by whichadjust the red and blue values of the actual RGB signature.

These adjusted values, instead of the original values, are compared withthe golden wafer signature from the new tool. Based on this comparison,the gain level control of the new tool is used to adjust the gain levelaccordingly. For example, at its current red gain level, the new tooldetected R=117 instead of 118.4. Thus, the red detector gain control ofthe new tool is adjusted until the two values correspond. Similarly, theblue detector gain level control is adjusted until the new tool detectsa blue value of B=157. The detection of golden wafer images and theresulting gain level adjustments can be iteratively repeated until thetwo signature values are substantially equal. By this method, the newtool is matched to the first tool.

The above-described methods for adjusting different image signatures andcalculating factors by which to adjust a gain-level setting areadvantageously implemented as executable computer code that controls theoperation of a microprocessor or computer during execution thereof. Thiscode can be stored on a physical medium such as a disk or tape or can betransmitted signals that travel over various communications media. FIG.6 provides a general description of a computer system that can executesuch code and interface with ADI tools and other photolithographyequipment.

Computer system 600 includes a bus 602 or other communication mechanismfor communicating information, and a processor 604 coupled with the bus602 for processing information. Computer system 600 also includes a mainmemory 606, such as random access memory or other dynamic storagedevice, coupled to the bus 602 for storing information and instructionsto be executed by the processor 604. Main memory 606 also may be usedfor storing temporary variables or other intermediate information duringexecution of instructions to be executed by the processor 604. Computersystem 600 further includes a read only memory 608 or other staticstorage device coupled to the bus 602 for storing static information andinstruction for the processor 604. A storage device 610, such as amagnetic or optical disk, is provided and coupled to the bus 602 forstoring information and instructions.

Computer system 600 may be coupled via the bus 602 to a display 612 fordisplaying information to a computer user. An input device 614, such asa keyboard, including alphanumeric or other keys, is coupled to the bus602 for communicating information and command selections to theprocessor 604. Another type of user input device is a cursor control616, such as a mouse, a trackball, or cursor direction keys forcommunicating direction information and command selections to theprocessor 604 and for controlling cursor movement on the display 612.The computer system 600 operates in response to processor 604 executingone or more sequences of one or more instructions contained in mainmemory 606. Such instructions may be read into main memory 606 fromanother computer-readable medium, such as storage device 610. Executionof the sequences of instructions contained in main memory 606 causesprocessor 604 to perform the process steps described herein. One or moreprocessors in a multi-processing arrangement may also be employed toexecute the sequences of instructions contained in main memory 606. Inalternative embodiments, hard-wired circuitry may be used in place of orin combination with software instructions to implement the invention.Thus, embodiments of the invention are not limited to any specificcombination of hardware circuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to processor 604 forexecution. Such a medium may take many forms, including but not limitedto non-volatile media, volatile media, and transmission media.Non-volatile media include, for example, optical or magnetic disks, suchas storage device 610. Volatile media include dynamic memory, such asmain memory 606. Transmission media include coaxial cables, copper wire,and fiber optics, including the wires that comprise bus 602.Transmission media can also take the form of acoustic or light waves,such as those generated during radio frequency (RF) and infrared (IR)data communications. Common forms of computer-readable media include,for example, a floppy disk, a flexible disk, hard disk, magnetic tape,any other magnetic medium, a CD-ROM, DVD, any other optical medium,punch cards, paper tape, any other physical medium with patterns ofholes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip orcartridge, a carrier wave as described hereinafter, or any other mediumfrom which a computer can read.

Various forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to processor 604 forexecution. For example, the instructions may initially be borne on amagnetic disk of a remote computer. The remote computer can load the,instructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 600 canreceive the data on the telephone line and use an infrared transmitterto convert the data to an infrared signal. An infrared detector coupledto bus 602 can receive the data carried in the infrared signal and placethe data on bus 602. Bus 602 carries the data to main memory 606, fromwhich processor 604 retrieves and executes the instructions. Theinstructions received by main memory 606 may optionally be stored onstorage device 610 either before or after execution by processor 604.

Computer system 600 also includes a communication interface 618 coupledto bus 602. Communication interface 618 provides a two-way datacommunication coupling to a network link 620 that is connected to alocal network 622. For example, communication interface 618 may be anintegrated services digital network (ISDN) card or a modem to provide adata communication connection to a corresponding type of telephone line.As another example, communication interface 618 may be a local areanetwork (LAN) card to provide a data communication connection to acompatible LAN. Wireless links may also be implemented. In any suchimplementation, communication interface 618 sends and receiveselectrical, electromagnetic or optical signals that carry digital datastreams representing various types of information.

Network link 620 typically provides data communication through one ormore networks to other data devices. For example, network link 620 mayprovide a connection through local network 622 to a host computer 624 orto data equipment operated by an Internet Service Provider (ISP) 626.ISP 626 in turn provides data communication services through the worldwide packet data communication network, now commonly referred to as the“Internet” 628. Local network 622 and Internet 628 both use electrical,electromagnetic or optical signals that carry digital data streams. Thesignals through the various networks and the signals on network link 620and through communication interface 618, which carry the digital data toand from computer system 600, are exemplary forms of carrier wavestransporting the information.

Computer system 600 can send messages and receive data, includingprogram code, through the network(s), network link 620, andcommunication interface 618. In the Internet example, a server 630 mighttransmit a requested code for an application program through Internet628, ISP 626, local network 622 and communication interface 618. Inaccordance with the invention, one such downloaded application providesfor hosting distributed objects as described herein. The received codemay be executed by processor 604 as it is received, and/or stored instorage device 610, or other non-volatile storage for later execution.In this manner, computer system 600 may obtain application code in theform of a carrier wave.

Although the present invention has been described and illustrated indetail, it is clearly understood that the same is by way of illustrationand example only and is not to be taken by way of limitation, the spiritand scope of the present invention being limited by the terms of theappended claims and their equivalents.

1. A method for inspecting a photolithographically processed wafer,comprising the steps of: determining a first image signature of a goldenwafer using a first lamp at a first intensity; determining a secondimage signature of the processed wafer using a second lamp at a secondintensity; adjusting the first image signature based on a differencebetween the first intensity and the second intensity to generate anadjusted golden wafer signature wherein the difference is substantiallyequal to a respective value of a single color of the second imagesignature subtracted from a respective value of a single color of thefirst image signature; determining a respective multiple color signatureof the golden wafer at each of a plurality of different setting valuesusing the first lamp; calculating a color slope corresponding to achange in the respective color values for said single color and aplurality of other colors of said multiple color signature as comparedto a change in the setting values; normalizing the slopes of each ofsaid other colors with respect to said slope of said single color togenerate an adjustment factor for each of said other colors; andgenerating a defect confidence value by comparing the second imagesignature with the golden wafer signature as adjusted by said adjustmentfactors.
 2. The method according to claim 1, wherein the first imagesignature and the second image signature are each a RGB signature. 3.The method according to claim 2, wherein each of the first imagesignature and the second image signature has a respective red value,green value, and blue value.
 4. The method according to claim 3, whereinthe difference is substantially equal to the respective green value ofthe second image signature subtracted from the respective green value ofthe first image signature.
 5. The method according to claim 4, furthercomprising the steps of: determining a respective RGB signature of thegolden wafer at each of a plurality of different setting values usingthe first lamp; calculating a red slope corresponding to a change in therespective red values as compared to a change in the setting values;calculating a green slope corresponding to a change in the respectivegreen values as compared to a change in the setting values; andcalculating a blue slope corresponding to a change in the respectiveblue values as compared to a change in the setting values.
 6. The methodaccording to claim 1, further comprising the step of: selecting thesecond intensity based on an inspection recipe.
 7. The method accordingto claim 6, wherein the inspection recipe identifies the firstintensity.
 8. A method for inspecting a photolithographically processedwafer, comprising the steps of: determining a first image signature of agolden wafer using a first lamp at a first intensity; determining asecond image signature of the processed wafer using a second lamp at asecond intensity; adjusting the first image signature based on adifference between the first intensity and the second intensity togenerate an adjusted golden wafer signature; and generating a defectconfidence value by comparing the second image signature with theadjusted golden wafer signature; the first image signature and thesecond image signature each being a RGB signature; each of the firstimage signature and the second image signature having a respective redvalue, green value, and blue value; the difference being substantiallyequal to the respective green value of the second image signaturesubtracted from the respective green value of the first image signature;determining a respective RGB signature of the golden wafer at each of aplurality of different setting values using the first lamp; calculatinga red slope corresponding to a change in the respective red values ascompared to a change in the setting values; calculating a green slopecorresponding to a change in the respective green values as compared toa change in the setting values; calculating a blue slope correspondingto a change in the respective blue values as compared to a change in thesetting values; normalizing the red slope with respect to the greenslope to generate a red adjustment factor; and normalizing the blueslope with respect to the green slope to generate a blue adjustmentfactor.
 9. The method according to claim 8, wherein the step ofadjusting further includes the steps of: adjusting the respective redvalue of the first image signature based on the difference and the redadjustment factor; and adjusting the respective blue value of the firstimage signature based on the difference and the blue adjustment factor.10. A method for inspecting a photolithographically processed wafer,comprising the steps of: determining a first image signature of a goldenwafer using a first lamp at a first intensity; determining a secondimage signature of the processed wafer using a second lamp at a secondintensity; adjusting the first image signature based on a differencebetween the first intensity and the second intensity to generate anadjusted golden wafer signature; generating a defect confidence value bycomparing the second image signature with the adjusted golden wafersignature; selecting the second intensity based on an inspection recipewherein the inspection recipe identifies the first intensity; andselecting one of a plurality of different intensity settings for thesecond lamp that is closest to the first intensity.
 11. A method forinspecting a photolithographically processed wafer after a develop step,comprising the steps of: determining a first RGB signature of a goldenwafer using a first lamp at a first intensity; determining a second RGBsignature of the processed wafer using a second lamp at a secondintensity; adjusting the first RGB signature based on a differencebetween the first intensity and the second intensity to generate anadjusted golden wafer signature; and generating a defect confidencevalue by comparing the second RGB signature with the adjusted goldenwafer signature; the adjusting step including: calculating a rate ofchange in the first RGB signature due to a unit change of lampintensity; and calculating an amount to adjust the first RGB signaturebased on the calculated rate of change and the difference between thefirst intensity and the second intensity.
 12. The method according toclaim 11, wherein each RGB signature has a respective red value, greenvalue, and blue value.
 13. The method according to claim 12, wherein thedifference is substantially equal to the respective green value of thesecond RGB signature subtracted from the respective green value of thefirst RGB signature.
 14. The method according to claim 13, furthercomprising the steps of: determining a respective RGB signature of thegolden wafer at each of a plurality of different setting values usingthe first lamp; calculating a red slope corresponding to a change in therespective red values as compared to a change in the setting values;calculating a green slope corresponding to a change in the respectivegreen values as compared to a change in the setting values; andcalculating a blue slope corresponding to a change in the respectiveblue values as compared to a change in the setting values.
 15. Themethod according to claim 14, further comprising the steps of:normalizing the red slope with respect to the green slope to generate ared adjustment factor; and normalizing the blue slope with respect tothe green slope to generate a blue adjustment factor.
 16. The methodaccording to claim 11, further comprising the step of: selecting thesecond intensity based on an inspection recipe.
 17. The method accordingto claim 16, wherein the inspection recipe identifies the firstintensity.
 18. The method according to claim 17, further comprising thestep of: A method for inspecting a photolithographically processed waferafter a develop step, comprising the steps of: determining a first RGBsignature of a golden wafer using a first lamp at a first intensity;determining a second RGB signature of the processed wafer using a secondlamp at a second intensity; adjusting the first RGB signature based on adifference between the first intensity and the second intensity togenerate an adjusted golden wafer signature; and generating a defectconfidence value by comparing the second RGB signature with the adjustedgolden wafer signature; selecting the second intensity based on aninspection recipe, wherein the inspection recipe identifies the firstintensity; and selecting one of a plurality of different intensitysettings for the second lamp that is closest to the first intensity. 19.A method for inspecting a photolithographically processed wafer after adevelop step, comprising the steps of: determining a first RGB signatureof a golden wafer using a first lamp at a first intensity; determining asecond RGB signature of the processed wafer using a second lamp at asecond intensity; adjusting the first RGB signature based on adifference between the first intensity and the second intensity togenerate an adjusted golden wafer signature; and generating a defectconfidence value by comparing the second RGB signature with the adjustedgolden wafer signature; each RGB signature having a respective redvalue, green value, and blue value; the difference being substantiallyequal to the respective green value of the second RGB signaturesubtracted from the respective green value of the first RGB signature;determining a respective RGB signature of the golden wafer at each of aplurality of different setting values using the first lamp; calculatinga red slope corresponding to a change in the respective red values ascompared to a change in the setting values; calculating a green slopecorresponding to a change in the respective green values as compared toa change in the setting values; calculating a blue slope correspondingto a change in the respective blue values as compared to a change in thesetting values; normalizing the red slope with respect to the greenslope to generate a red adjustment factor; and normalizing the blueslope with respect to the green slope to generate a blue adjustmentfactor; the step of adjusting further including: adjusting therespective red value of the first RGB signature based on the differenceand the red adjustment factor; and adjusting the respective blue valueof the first RGB signature based on the difference and the blueadjustment factor.